Use AgentMarket.get_positions in microchain Function (#91)

* Use AgentMarket.get_positions in microchain Function

* Decimal -> float

* Bump PMAT version

main.py

@@ -1,5 +1,3 @@
-from decimal import Decimal
-
 import typer
 from loguru import logger
 from prediction_market_agent_tooling.markets.agent_market import SortBy
@@ -47,9 +45,7 @@ def main(
         logger.info(
             f"Placing bet with position {pma.utils.parse_result_to_str(result)} on market '{market.question}'"
         )
-        amount = Decimal(
-            input(f"How much do you want to bet? (in {market.currency}): ")
-        )
+        amount = float(input(f"How much do you want to bet? (in {market.currency}): "))
         market.place_bet(
             amount=market.get_bet_amount(amount),
             outcome=result,

prediction_market_agent/agents/known_outcome_agent/deploy.py

@@ -1,6 +1,5 @@
 import random
 import typing as t
-from decimal import Decimal
 
 from loguru import logger
 from prediction_market_agent_tooling.deploy.agent import DeployableAgent
@@ -82,6 +81,6 @@ def answer_binary_market(self, market: AgentMarket) -> bool | None:
 
     def calculate_bet_amount(self, answer: bool, market: AgentMarket) -> BetAmount:
         if isinstance(market, OmenAgentMarket):
-            return BetAmount(amount=(Decimal(1.0)), currency=market.currency)
+            return BetAmount(amount=1.0, currency=market.currency)
         else:
             raise NotImplementedError("This agent only supports xDai markets")

prediction_market_agent/agents/microchain_agent/functions.py

@@ -1,15 +1,9 @@
 import typing as t
-from decimal import Decimal
 
-from eth_utils import to_checksum_address
 from microchain import Function
 from prediction_market_agent_tooling.markets.agent_market import AgentMarket
 from prediction_market_agent_tooling.markets.data_models import Currency, TokenAmount
 from prediction_market_agent_tooling.markets.markets import MarketType
-from prediction_market_agent_tooling.markets.omen.data_models import OmenUserPosition
-from prediction_market_agent_tooling.markets.omen.omen_subgraph_handler import (
-    OmenSubgraphHandler,
-)
 
 from prediction_market_agent.agents.microchain_agent.utils import (
     MechResult,
@@ -207,7 +201,7 @@ def __call__(self, market_id: str, amount: float) -> str:
         )
         market.buy_tokens(
             outcome=self.outcome_bool,
-            amount=TokenAmount(amount=Decimal(amount), currency=self.currency),
+            amount=TokenAmount(amount=amount, currency=self.currency),
         )
         after_balance = market.get_token_balance(
             user_id=self.user_address,
@@ -263,7 +257,7 @@ def __call__(self, market_id: str, amount: float) -> str:
 
         market.sell_tokens(
             outcome=self.outcome_bool,
-            amount=TokenAmount(amount=Decimal(amount), currency=self.currency),
+            amount=TokenAmount(amount=amount, currency=self.currency),
         )
 
         after_balance = market.get_token_balance(
@@ -314,25 +308,32 @@ def description(self) -> str:
     def example_args(self) -> list[str]:
         return []
 
-    def __call__(self) -> Decimal:
+    def __call__(self) -> float:
         return get_balance(market_type=self.market_type).amount
 
 
-class GetUserPositions(MarketFunction):
+class GetPositions(MarketFunction):
+    def __init__(self, market_type: MarketType) -> None:
+        self.user_address = MicrochainAPIKeys().bet_from_address
+        super().__init__(market_type=market_type)
+
     @property
     def description(self) -> str:
         return (
-            "Use this function to fetch the markets where the user has previously bet."
+            "Use this function to fetch the live markets where you have "
+            "previously bet, and the token amounts you hold for each outcome."
         )
 
     @property
     def example_args(self) -> list[str]:
-        return ["0x2DD9f5678484C1F59F97eD334725858b938B4102"]
+        return []
 
-    def __call__(self, user_address: str) -> list[OmenUserPosition]:
-        return OmenSubgraphHandler().get_user_positions(
-            better_address=to_checksum_address(user_address)
+    def __call__(self) -> list[str]:
+        self.user_address = MicrochainAPIKeys().bet_from_address
+        positions = self.market_type.market_class.get_positions(
+            user_id=self.user_address
         )
+        return [str(position) for position in positions]
 
 
 MISC_FUNCTIONS = [
@@ -352,5 +353,5 @@ def __call__(self, user_address: str) -> list[OmenUserPosition]:
     BuyNo,
     SellYes,
     SellNo,
-    GetUserPositions,
+    GetPositions,
 ]

prediction_market_agent/agents/microchain_agent/utils.py

@@ -2,7 +2,6 @@
 import tempfile
 import typing as t
 from contextlib import contextmanager
-from decimal import Decimal
 from enum import Enum
 
 from mech_client.interact import ConfirmationType, interact
@@ -94,7 +93,7 @@ def get_balance(market_type: MarketType) -> BetAmount:
     if market_type == MarketType.OMEN:
         # We focus solely on xDAI balance for now to avoid the agent having to wrap/unwrap xDAI.
         return BetAmount(
-            amount=Decimal(get_balances(MicrochainAPIKeys().bet_from_address).xdai),
+            amount=get_balances(MicrochainAPIKeys().bet_from_address).xdai,
             currency=currency,
         )
     else:

pyproject.toml

@@ -35,7 +35,7 @@ poetry = "^1.7.1"
 poetry-plugin-export = "^1.6.0"
 functions-framework = "^3.5.0"
 cron-validator = "^1.0.8"
-prediction-market-agent-tooling = { version = "^0.13.2", extras = ["langchain", "google"] }
+prediction-market-agent-tooling = { version = "^0.14.1", extras = ["langchain", "google"] }
 pydantic-settings = "^2.1.0"
 autoflake = "^2.2.1"
 isort = "^5.13.2"

tests/agents/microchain/test_functions.py

@@ -4,7 +4,6 @@
 from microchain.functions import Reasoning, Stop
 from prediction_market_agent_tooling.markets.agent_market import AgentMarket
 from prediction_market_agent_tooling.markets.markets import MarketType
-from prediction_market_agent_tooling.tools.hexbytes_custom import HexBytes
 
 from prediction_market_agent.agents.microchain_agent.functions import (
     MARKET_FUNCTIONS,
@@ -14,7 +13,7 @@
     GetBalance,
     GetMarketProbability,
     GetMarkets,
-    GetUserPositions,
+    GetPositions,
     MarketFunction,
     PredictProbabilityForQuestionLocal,
     PredictProbabilityForQuestionRemote,
@@ -64,18 +63,10 @@ def test_replicator_has_balance_gt_0(market_type: MarketType) -> None:
 
 
 @pytest.mark.parametrize("market_type", [MarketType.OMEN])
-def test_agent_0_has_bet_on_market(market_type: MarketType) -> None:
-    user_positions = GetUserPositions(market_type=market_type)(AGENT_0_ADDRESS)
-    # Assert 3 conditionIds are included
-    expected_condition_ids = [
-        HexBytes("0x9c7711bee0902cc8e6838179058726a7ba769cc97d4d0ea47b31370d2d7a117b"),
-        HexBytes("0xe2bf80af2a936cdabeef4f511620a2eec46f1caf8e75eb5dc189372367a9154c"),
-        HexBytes("0x3f8153364001b26b983dd92191a084de8230f199b5ad0b045e9e1df61089b30d"),
-    ]
-    unique_condition_ids: list[HexBytes] = sum(
-        [u.position.conditionIds for u in user_positions], []
-    )
-    assert set(expected_condition_ids).issubset(unique_condition_ids)
+def test_get_positions(market_type: MarketType) -> None:
+    get_positions = GetPositions(market_type=market_type)
+    positions = get_positions()
+    assert len(positions) > 0
 
 
 @pytest.mark.parametrize("market_type", [MarketType.OMEN])